1. Field of the Invention
The present invention relates to a boundary line recognition apparatus capable of detecting a boundary line on a driving lane of a vehicle in order to assist the driver of the vehicle.
2. Description of the Related Art
There is a conventional driving lane departing warning apparatus to assist a vehicle driver capable of providing a warning to the vehicle driver when a vehicle departs from the current driving lane. In general, such a conventional apparatus is comprised of an image acquiring part, an image processing part, and a warning generation part. The image acquiring part has one or more on-vehicle cameras. The image processing part processes image data transferred from the image acquiring part. The warning generation part generates a warning based on the processing result transferred from the image processing part, and provides the generated warning to the vehicle driver.
The image processing part detects or estimates a boundary line of a driving lane based on image data obtained by the image acquiring part. The warning generation part calculates a right distance measured from the vehicle to a right-side boundary line of the driving lane, and a left distance measured from the vehicle to a left-side boundary line of the driving lane. When one of the calculated distances is not more than a predetermined threshold value, in other words, when the driver's vehicle approaches the boundary line within a distance indicated by the threshold value, the warning generation part generates and provides a warning to the vehicle driver.
In such an apparatus capable of providing a warning to the vehicle driver when the vehicle departs from the current driving lane, an important problem is a wrong detection based on noise. For example, there are various error sources to generate such a wrong detection, for example, a dirty mark on a driving lane, traffic signs painted on a driving lane, a light reflected from a puddle on a road, a shadow of the driver's vehicle, a shadow of a following vehicle, etc.
In order to avoid such a wrong detection caused by the influence from those error sources and extract a target boundary line as a target in warning by eliminating the influence of noise, there has been proposed a conventional technique to calculate a degree of probability of each boundary line candidate which contains such noise, and selects the candidate having a highest probability.
For example, Japanese patent laid open publication No. JP 2005-18148 discloses such a conventional technique to calculate the target candidate having a highest probability based on the number of boundary line candidates, a strength of an edge of the boundary line candidate, a contrast in brightness of an area around the boundary line candidate, etc.
However, the conventional technique disclosed in JP 2005-18148 needs performing an optimum process suitable for each of: (a) the number of boundary line candidates; (b) an edge strength of a boundary line candidate; and (c) a contrast in brightness of an area around the boundary line candidate, etc., and finally combining the results of those process (a), (b), and (c).
This needs complex processing, and makes it difficult to improve those processes and add an additional function to the processes. That is, in order to improve a robust control to perform image data processing, it is generally required to improve each process and add an additional process. However, because combining each of the functions needs performing a complex process, this makes it difficult to perform the combination of the processes and the functions.